Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm
Abstract In this study, we propose an underwater localization method based on an improved invasive weed optimization algorithm to accurately locate moving sources in underwater sensor networks. First, the Lévy flight model is introduced into the invasive weed optimization algorithm to enhance its gl...
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| Format: | Article |
| Language: | English |
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Wiley
2022-05-01
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| Series: | IET Signal Processing |
| Online Access: | https://doi.org/10.1049/sil2.12091 |
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| _version_ | 1832559684982145024 |
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| author | Yunhang Lin Zhenkai Zhang Hamid Esmaeili Najafabadi |
| author_facet | Yunhang Lin Zhenkai Zhang Hamid Esmaeili Najafabadi |
| author_sort | Yunhang Lin |
| collection | DOAJ |
| description | Abstract In this study, we propose an underwater localization method based on an improved invasive weed optimization algorithm to accurately locate moving sources in underwater sensor networks. First, the Lévy flight model is introduced into the invasive weed optimization algorithm to enhance its global search ability and avoid falling into local optima. At the same time, under the condition that the observed noise of each observation is Gaussian noise and does not consider the influence of other error factors, the localization error is adopted as the objective function to obtain an initial estimate for the unknown source parameter. Then, the obtained initial estimates of the target position and velocity as well as the target parameter error are utilized to construct a new localization model. Finally, the precise position of the source and its velocity are obtained according to the weighted least square method. The performance of the algorithm is verified by comparing it with the Cramér–Rao Lower Bound (CRLB). Results from simulations indicate that the algorithm proposed in this paper has excellent localization accuracy compared to existing methods and achieves results close to the CRLB. |
| format | Article |
| id | doaj-art-3eea03a7b1474688a6fcc35faabf84f8 |
| institution | Kabale University |
| issn | 1751-9675 1751-9683 |
| language | English |
| publishDate | 2022-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj-art-3eea03a7b1474688a6fcc35faabf84f82025-02-03T01:29:25ZengWileyIET Signal Processing1751-96751751-96832022-05-0116329930910.1049/sil2.12091Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithmYunhang Lin0Zhenkai Zhang1Hamid Esmaeili Najafabadi2Department of Electronics and Information Jiangsu University of Science and Technology Zhenjiang Jiangsu ChinaDepartment of Electronics and Information Jiangsu University of Science and Technology Zhenjiang Jiangsu ChinaDepartment of Electrical and Computer Engineering University of Calgary Calgary Alberta CanadaAbstract In this study, we propose an underwater localization method based on an improved invasive weed optimization algorithm to accurately locate moving sources in underwater sensor networks. First, the Lévy flight model is introduced into the invasive weed optimization algorithm to enhance its global search ability and avoid falling into local optima. At the same time, under the condition that the observed noise of each observation is Gaussian noise and does not consider the influence of other error factors, the localization error is adopted as the objective function to obtain an initial estimate for the unknown source parameter. Then, the obtained initial estimates of the target position and velocity as well as the target parameter error are utilized to construct a new localization model. Finally, the precise position of the source and its velocity are obtained according to the weighted least square method. The performance of the algorithm is verified by comparing it with the Cramér–Rao Lower Bound (CRLB). Results from simulations indicate that the algorithm proposed in this paper has excellent localization accuracy compared to existing methods and achieves results close to the CRLB.https://doi.org/10.1049/sil2.12091 |
| spellingShingle | Yunhang Lin Zhenkai Zhang Hamid Esmaeili Najafabadi Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm IET Signal Processing |
| title | Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm |
| title_full | Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm |
| title_fullStr | Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm |
| title_full_unstemmed | Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm |
| title_short | Underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm |
| title_sort | underwater source localization using time difference of arrival and frequency difference of arrival measurements based on an improved invasive weed optimization algorithm |
| url | https://doi.org/10.1049/sil2.12091 |
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